path = None

# Parameters
path = "/var/folders/wf/2fbzf4jd0ls3l98_561qjsxh0000gn/T/flyte-_sgm4nsk/raw/d97c85a1eb457c724c1e6901218ad5eb/tmp05uv7bor"

from dataclasses import asdict
from IPython.display import display
import pandas as pd
from PIL import Image

from methanesat.demos import IMAGES

Report

try:
    df = pd.read_parquet(path)
except:
    df = pd.DataFrame([asdict(img) for img in IMAGES])
df["correct"] = ((df.prediction > 0.5) == df.label).astype(int)
df.sort_values(by="correct")[["label", "prediction", "description"]]

	label	prediction	description
2	0.0	0.934557	This image is named img3.png and contains clouds
0	1.0	0.960024	This image is named img1.png and contains meth...
1	1.0	0.933431	This image is named img2.png and contains meth...

accuracy = df["correct"].sum() / len(df) 
print(f"accuracy = {accuracy}")

accuracy = 0.6666666666666666

False Positives

for i, img in enumerate(IMAGES):
    if (img.prediction > 0.5) == 1 and img.label == 0.0:
        print(f"Image {i}")
        display(Image.open(img.file.download()))

Image 2

True Positives & Negatives

for i, img in enumerate(IMAGES):
    if (img.prediction > 0.5) == img.label:
        print(f"Image {i}")
        display(Image.open(img.file.download()))

Image 0

Image 1